{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Visualizing outliers with Boxplots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from sklearn.datasets import fetch_california_housing\n",
    "\n",
    "sns.set(style=\"darkgrid\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>MedInc</th>\n",
       "      <th>HouseAge</th>\n",
       "      <th>AveRooms</th>\n",
       "      <th>AveBedrms</th>\n",
       "      <th>Population</th>\n",
       "      <th>AveOccup</th>\n",
       "      <th>Latitude</th>\n",
       "      <th>Longitude</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>8.3252</td>\n",
       "      <td>41.0</td>\n",
       "      <td>6.984127</td>\n",
       "      <td>1.023810</td>\n",
       "      <td>322.0</td>\n",
       "      <td>2.555556</td>\n",
       "      <td>37.88</td>\n",
       "      <td>-122.23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>8.3014</td>\n",
       "      <td>21.0</td>\n",
       "      <td>6.238137</td>\n",
       "      <td>0.971880</td>\n",
       "      <td>2401.0</td>\n",
       "      <td>2.109842</td>\n",
       "      <td>37.86</td>\n",
       "      <td>-122.22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>7.2574</td>\n",
       "      <td>52.0</td>\n",
       "      <td>8.288136</td>\n",
       "      <td>1.073446</td>\n",
       "      <td>496.0</td>\n",
       "      <td>2.802260</td>\n",
       "      <td>37.85</td>\n",
       "      <td>-122.24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>5.6431</td>\n",
       "      <td>52.0</td>\n",
       "      <td>5.817352</td>\n",
       "      <td>1.073059</td>\n",
       "      <td>558.0</td>\n",
       "      <td>2.547945</td>\n",
       "      <td>37.85</td>\n",
       "      <td>-122.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3.8462</td>\n",
       "      <td>52.0</td>\n",
       "      <td>6.281853</td>\n",
       "      <td>1.081081</td>\n",
       "      <td>565.0</td>\n",
       "      <td>2.181467</td>\n",
       "      <td>37.85</td>\n",
       "      <td>-122.25</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   MedInc  HouseAge  AveRooms  AveBedrms  Population  AveOccup  Latitude  \\\n",
       "0  8.3252      41.0  6.984127   1.023810       322.0  2.555556     37.88   \n",
       "1  8.3014      21.0  6.238137   0.971880      2401.0  2.109842     37.86   \n",
       "2  7.2574      52.0  8.288136   1.073446       496.0  2.802260     37.85   \n",
       "3  5.6431      52.0  5.817352   1.073059       558.0  2.547945     37.85   \n",
       "4  3.8462      52.0  6.281853   1.081081       565.0  2.181467     37.85   \n",
       "\n",
       "   Longitude  \n",
       "0    -122.23  \n",
       "1    -122.22  \n",
       "2    -122.24  \n",
       "3    -122.25  \n",
       "4    -122.25  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# load the California House price data from Scikit-learn\n",
    "X, y = fetch_california_housing(return_X_y=True, as_frame=True)\n",
    "\n",
    "# display top 5 rows\n",
    "X.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 9 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "X.hist(bins=30, figsize=(12, 12))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x216 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# boxplot\n",
    "plt.figure(figsize=(8, 3))\n",
    "sns.boxplot(data=X[\"MedInc\"], orient=\"y\")\n",
    "plt.title(\"Boxplot\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_boxplot_and_hist(data, variable):\n",
    "    # creating a figure composed of two matplotlib.Axes objects (ax_box and ax_hist)\n",
    "    f, (ax_box, ax_hist) = plt.subplots(\n",
    "        2, sharex=True, gridspec_kw={\"height_ratios\": (0.50, 0.85)}\n",
    "    )\n",
    "\n",
    "    # assigning a graph to each ax\n",
    "    sns.boxplot(x=data[variable], ax=ax_box)\n",
    "    sns.histplot(data=data, x=variable, ax=ax_hist)\n",
    "\n",
    "    # Remove x axis name for the boxplot\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_boxplot_and_hist(X, \"MedInc\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "def find_limits(df, variable, fold):\n",
    "    q1 = df[variable].quantile(0.25)\n",
    "    q3 = df[variable].quantile(0.75)\n",
    "\n",
    "    IQR = q3 - q1\n",
    "\n",
    "    lower_limit = q1 - (IQR * fold)\n",
    "    upper_limit = q3 + (IQR * fold)\n",
    "\n",
    "    return lower_limit, upper_limit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-0.7063750000000004, 8.013024999999999)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# we find the limits\n",
    "\n",
    "lower_limit, upper_limit = find_limits(X, \"MedInc\", 1.5)\n",
    "lower_limit, upper_limit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_boxplot_and_hist(X, \"HouseAge\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-10.5, 65.5)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# we find the limits\n",
    "\n",
    "lower_limit, upper_limit = find_limits(X, \"HouseAge\", 1.5)\n",
    "lower_limit, upper_limit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_boxplot_and_hist(X, \"Population\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-620.0, 3132.0)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# we find the limits\n",
    "\n",
    "lower_limit, upper_limit = find_limits(X, \"Population\", 1.5)\n",
    "lower_limit, upper_limit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "fsml",
   "language": "python",
   "name": "fsml"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.5"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
